Artificial intelligence (AI) continues to evolve and propel businesses forward; however, the Life Science industry's adoption of these technologies is delayed in comparison with other industries. AI technologies have the ability to greatly reduce cost and time to market of products, especially when applied to and integrated with the process validation lifecycle. Due to the nature of the highly regulated industry, these technologies also introduce a number of challenges to the industry, particularly when it comes to validating these solutions. This presentation aims to demonstrate how developing AI solutions integrates with the process validation lifecycle, while demystifying some of the nuances around various AI solutions and terminology. It also works to lay out comparisons between AI, multivariate statistics, and traditional Continued Process Validation (CPV) methods; highlighting the benefits of each and use cases where each solution may be preferred.
Alyssa Burke (Wed,) studied this question.